Modelling and Simulation of a Redundant Agricultural Manipulator with Virtual Prototyping

A. Reddy, V. V. M. J. S. Chembuly, V. Rao
{"title":"Modelling and Simulation of a Redundant Agricultural Manipulator with Virtual Prototyping","authors":"A. Reddy, V. V. M. J. S. Chembuly, V. Rao","doi":"10.18196/jrc.v4i1.17121","DOIUrl":null,"url":null,"abstract":"The development of autonomous robots for agricultural applications includes motion planning, fruit picking, and collision avoidance with surrounding environments, and these become challenging tasks. For harvesting applications, robust control of the manipulator is needed for the effective motion of the robot. Several combinations of Proportional(P)- Integrative(I)- Derivative(D) controllers are modelled and a simulation study was performed for trajectory tracking of a redundant manipulator in virtual agricultural environments. The article presents a comprehensive study on kinematic modelling and dynamic control of redundant manipulator for fruit-picking applications in virtual environments. The collisions with surrounding environment were eliminated using ‘bounding box technique’. The joint variables are obtained by constructing Inverse Kinematics (IK) problem and are determined using a classical optimization technique. Different controllers are modelled in the ‘Simulink’ environment and are tuned to generate error-free trajectory tracking during harvesting. The task space locations (TSLs) are considered as via-points, and joint variables at each TSLs are obtained by Sequential Quadratic Programming (SQP) technique. Joint-level trajectories are generated using Quintic and B-spline polynomials. For effective trajectory tracking, torque variations are controlled using the PID and Feedforward (FF) controller. The dynamic simulations of the robot manipulator are performed in Simscape Multibody software. Results show that the during the trajectory tracking of the manipulator, the Feed-forward controller performs best with Quintic polynomial trajectory.","PeriodicalId":443428,"journal":{"name":"Journal of Robotics and Control (JRC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Robotics and Control (JRC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18196/jrc.v4i1.17121","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

The development of autonomous robots for agricultural applications includes motion planning, fruit picking, and collision avoidance with surrounding environments, and these become challenging tasks. For harvesting applications, robust control of the manipulator is needed for the effective motion of the robot. Several combinations of Proportional(P)- Integrative(I)- Derivative(D) controllers are modelled and a simulation study was performed for trajectory tracking of a redundant manipulator in virtual agricultural environments. The article presents a comprehensive study on kinematic modelling and dynamic control of redundant manipulator for fruit-picking applications in virtual environments. The collisions with surrounding environment were eliminated using ‘bounding box technique’. The joint variables are obtained by constructing Inverse Kinematics (IK) problem and are determined using a classical optimization technique. Different controllers are modelled in the ‘Simulink’ environment and are tuned to generate error-free trajectory tracking during harvesting. The task space locations (TSLs) are considered as via-points, and joint variables at each TSLs are obtained by Sequential Quadratic Programming (SQP) technique. Joint-level trajectories are generated using Quintic and B-spline polynomials. For effective trajectory tracking, torque variations are controlled using the PID and Feedforward (FF) controller. The dynamic simulations of the robot manipulator are performed in Simscape Multibody software. Results show that the during the trajectory tracking of the manipulator, the Feed-forward controller performs best with Quintic polynomial trajectory.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于虚拟样机的冗余农业机械臂建模与仿真
农业自主机器人的发展包括运动规划、水果采摘和与周围环境的碰撞避免,这些都成为具有挑战性的任务。在收获应用中,为了保证机器人的有效运动,需要对机械手进行鲁棒控制。对比例(P)-积分(I)-导数(D)控制器的几种组合进行了建模,并对虚拟农业环境中冗余机械手的轨迹跟踪进行了仿真研究。本文对虚拟环境中用于水果采摘的冗余机械手的运动学建模和动态控制进行了全面的研究。使用“边界盒技术”消除了与周围环境的碰撞。通过构造逆运动学问题得到关节变量,并用经典的优化方法确定关节变量。不同的控制器在“Simulink”环境中建模,并在收获过程中进行调整以产生无错误的轨迹跟踪。将任务空间位置(TSLs)视为中点,利用序列二次规划(SQP)技术得到每个TSLs上的联合变量。利用五次多项式和b样条多项式生成关节级轨迹。为了实现有效的轨迹跟踪,利用PID和前馈(FF)控制器控制转矩变化。在Simscape Multibody软件中对该机械手进行了动力学仿真。结果表明,在机械臂的轨迹跟踪过程中,前馈控制器对五次多项式轨迹的跟踪效果最好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
6.30
自引率
0.00%
发文量
0
期刊最新文献
Efficient Path Planning Algorithm for Mobile Robots Performing Floor Cleaning Like Operations Adaptive Cruise Control of the Autonomous Vehicle Based on Sliding Mode Controller Using Arduino and Ultrasonic Sensor Development of Microclimate Data Recorder on Coffee-Pine Agroforestry Using LoRaWAN and IoT Technology Using Learning Focal Point Algorithm to Classify Emotional Intelligence Enhanced Trajectory Tracking of 3D Overhead Crane Using Adaptive Sliding-Mode Control and Particle Swarm Optimization
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1